[Hiring] Lead Intelligent Solutions Engineer @McKesson

Role Description

The Lead Intelligent Solutions Engineer is a senior, hands-on technical builder-leader accountable for delivering AI and intelligent automation solutions end-to-end, from problem framing through production deployment and sustained value realization. This role personally designs, builds, and scales LLM- and agent-based automations while owning solution architecture, technical quality, delivery outcomes, and enterprise standards.

This position requires deep technical expertise, strong architectural judgment, and the ability to independently drive complex, ambiguous initiatives to completion. The role is not oversight-only; it is focused on custom AI development, intelligent automation, and solution execution using large language models, agents, orchestration frameworks, and enterprise integrations.

In addition, this role is expected to evangelize and engage the business, translating opportunities and problems into tangible, trusted, production-ready AI solutions that measurably improve productivity, quality, cycle time, and decision-making across SCRI.

This is a remote position based in the United States. Relocation assistance and visa sponsorship are not available.

Duties include but are not limited to:

• Hands-On AI & Intelligent Automation Development (Primary Accountability)
• Independently design, build, and maintain:
  • AI prompts and prompt libraries
  • LLM based agents and copilots
  • Chatbots, automation scripts, and end-to-end intelligent workflows
• Lead rapid prototyping and experimentation; convert successful pilots into scalable, production-grade solutions
• Own the day-to-day technical health of deployed solutions, including monitoring, troubleshooting, performance tuning, and reliability improvements
• Build and maintain robust integrations with enterprise platforms using APIs, services, data pipelines, and workflow orchestration tools
• End-To-End Solution Architecture & Delivery Ownership
• Serve as the end-to-end AI solution architect for assigned initiatives, making architectural decisions and implementing them hands-on
• Define and standardize solution patterns for:
  • Agent architectures (RAG, tool calling, multi-agent orchestration)
  • Integration and data flow design
  • Environmental promotion and deployment strategies (dev/test/prod)
• Own delivery planning with clearly defined value metrics, success criteria, and timelines
• Proactively identify technical risks, trade-offs, and dependencies and drive resolution
• Use Case Execution & Enterprise Impact
• Lead execution for high-impact, enterprise-level AI and automation use cases, particularly complex or manual processes with measurable value potential
• Translate loosely defined business problems into durable, production-ready AI solutions
• Typical use cases include, but are not limited to:
  • LLM-based agents for case intake, triage, summarization, and decision support
  • Intelligent document processing across emails, PDFs, forms, and unstructured content
  • Workflow automation for finance, operations, compliance, research, or shared services
  • Embedded AI assistants integrated into enterprise systems to reduce manual effort, errors, and cycle time
• Partner closely with business owners to validate outputs, refine logic, and ensure solutions are adopted, trusted, and operationalized
• Governance, Security & Compliance (Lead-Level Accountability)
• Ensure all solutions comply with enterprise AI governance standards, ethical AI principles, and corporate policies
• Design and implement secure-by-default solutions, including documentation, traceability, monitoring, and audit readiness
• Anticipate and mitigate risks related to data privacy, access control, model behavior, hallucinations, bias, and operational resilience
• Partner with architecture, security, and data governance teams to ensure compliant solution design, especially within regulated environments
• Evangelism, Enablement & Technical Leadership
• Evangelize AI and intelligent automation capabilities across the organization by:
  • Engaging business stakeholders
  • Translating opportunities into concrete solution concepts
  • Demonstrating value through working solutions
• Produce high-quality technical documentation, user guides, and SOPs
• Lead hands-on enablement sessions, workshops, and knowledge transfer to drive adoption
• Act as a technical mentor and thought leader, influencing standards, patterns, and best practices across AI and automation initiatives
• Collaborate with business and technology partners to continuously improve AI-enhanced workflows

Qualifications

• Bachelor's Degree required, Master's Degree preferred
• At least 7 years of experience in machine learning

Requirements

• Proven experience delivering complex, production-grade AI and automation solutions as a hands-on builder
• Deep proficiency in prompt engineering and applying Generative AI to enterprise workflows
• Strong programming skills (typically Python and/or JavaScript) with experience in APIs, data transformation, version control, and deployment practices
• Demonstrated experience building agentic AI solutions, including RAG architectures, orchestration frameworks, and tool-calling patterns
• Experience with Microsoft AI ecosystem tools (e.g., Copilot Studio, Power Platform, Azure AI / Azure OpenAI) strongly preferred
• Ability to rapidly prototype while maintaining enterprise-grade security, reliability, and governance
• Demonstrated ability to operate as a senior, end-to-end AI solution architect while remaining hands-on
• Comfortable owning ambiguous, high-visibility initiatives with minimal direction
• Strong stakeholder influence skills; able to align technical decisions with business outcomes in a matrixed environment
• Track record of translating concepts into shipped, adopted, enterprise solutions

Benefits

• Comprehensive benefits to support physical, mental, and financial well-being
• Competitive compensation package determined by performance, experience, skills, equity, regular job market evaluations, and geographical markets
• Other compensation, such as an annual bonus or long-term incentive opportunities may be offered